The Fundamentals of Quality of Earnings (QoE)
Unlike a statutory audit, which verifies that financial statements comply with accounting standards (GAAP or IFRS), an earnings quality analysis focuses on the economic substance of the business. The primary objective is to arrive at a "normalized" or "representative" EBITDA that reflects what the business will generate under new ownership.
According to the Bain & Company 2026 Global M&A Report, financial due diligence rigor has intensified as interest rates and valuation multiples remain under scrutiny. Investors are no longer accepting management's adjusted EBITDA at face value. They require a granular breakdown of every adjustment, supported by primary source documentation.
- Sustainability: Can the current level of earnings be maintained without significant new capital expenditure or changes in market conditions?
- Accuracy: Do the reported figures align across management accounts, audited financials, and tax filings?
- Composition: Is the profit driven by core operations or by non-operating gains, such as the sale of assets or currency fluctuations?
EBITDA Normalization and Common Adjustments
Normalization is the process of adjusting the historical EBITDA to remove items that are not expected to recur or are not reflective of the core business operations. This is where the majority of value is found or lost during financial due diligence.
Common adjustments fall into several categories, ranging from obvious one-time costs to subtle accounting shifts. A robust analysis requires triangulating data across multiple sources. For instance, Plausity's AI Analysis Engine can cross-reference management accounts against audited financials and bank statements to detect discrepancies that suggest aggressive revenue recognition or deferred maintenance.
Common EBITDA Adjustments Table| Adjustment Category | Description | Impact on EBITDA |
|---|---|---|
| Non-recurring Expenses | One-time legal fees, restructuring costs, or relocation expenses. | Positive (Add-back) |
| Owner/Management Compensation | Salaries or bonuses above or below market rates in founder-led firms. | Variable |
| Personal Expenses | Non-business related travel, vehicles, or club memberships. | Positive (Add-back) |
| Pro-forma Adjustments | Full-year impact of new contracts or recent acquisitions. | Positive |
| Accounting Policy Changes | Shifts in revenue recognition or capitalization of R&D. | Variable |
Identifying Red Flags in Earnings Quality
Experienced deal professionals look for patterns that indicate "earnings management"—the practice of using accounting flexibility to smooth out earnings or meet specific targets. Identifying these red flags early in the process can prevent overpayment or provide leverage for price negotiations.
One common scenario involves the "pull-forward" of revenue. A company might offer deep discounts to customers at the end of a quarter to hit targets, effectively stealing revenue from future periods. Another risk is the under-reporting of expenses, such as delaying necessary repairs or capitalizing costs that should be expensed immediately. These issues are often buried in the footnotes of thousands of documents.
- Revenue Concentration: High dependency on a single customer (e.g., >20% of revenue) creates significant risk if that contract is nearing expiration.
- Working Capital Anomalies: A sudden decrease in accounts payable or an increase in inventory levels relative to sales can signal cash flow stress.
- Capitalization of Operating Expenses: Treating routine maintenance as a capital improvement to artificially inflate EBITDA.
The Role of AI in Financial Due Diligence
The traditional approach to financial DD involves analysts manually extracting data from PDFs into Excel models. This process is prone to error and limits the scope of the analysis. Plausity transforms this workflow by automating the end-to-end process, from VDR ingestion to investor-ready reporting.
Plausity's AI-native workspace runs 9 workstreams simultaneously, including Financial, Commercial, and Tax DD. This allows for cross-workstream risk mapping. For example, a legal finding regarding a pending litigation can be immediately mapped to the financial workstream to assess its impact on contingent liabilities and earnings quality. This level of synthesis is difficult to achieve in siloed, manual processes.
A Big Four Advisory partner reported that using Plausity cut their commercial DD timeline from three weeks to five days on a mid-market transaction. This speed does not come at the expense of rigor. Every finding in Plausity is linked to the specific document, page, and paragraph, providing full source traceability and confidence scoring. This allows senior advisors to focus on high-level conclusions rather than data hunting.
From Analysis to Investor-Ready Reporting
The final deliverable of an earnings quality analysis is the DD report. This document must be precise, verified, and ready for presentation to investment committees or boards. Traditional reporting involves significant manual formatting, which consumes valuable senior advisor time.
Plausity's Report Builder dynamically generates executive briefings, red flag summaries, and full DD reports based on the findings surfaced during the analysis. These reports are not just raw data; they are structured narratives that highlight material risks and financial impacts. Users can export these deliverables to Word, PowerPoint, or PDF with custom branding.
- Source Traceability: Every figure in the report can be traced back to the original VDR document with a single click.
- Post-Acquisition Roadmaps: Findings are converted into scored, prioritized 100-day plans with financial impact estimates.
- Enterprise Security: All data is protected by SOC 2 Type II and ISO 27001 certifications, ensuring that sensitive financial information remains confidential.
